Better design decisions through operational modeling during the early design phases
Better design decisions through operational modeling during the early design phases
This work presents an operational simulation based on a unique mission ontology that enables recreating any aviation scenario using a small set of parameters. The tool is designed to suit the early design phases where time pressures, uncertainties and knowledge gaps peak. It is embedded in a stack of software allowing early design phase optimization based on operational constraints. This stack was used to design and build several Unmanned Aerial Vehicles. Two case studies demonstrate how the tool can act as a decision support or optimization tool, leading to improved designs and better operations. It is found that early design decisions can be based on a more rigorous analysis and that it is possible to optimize both the design and the operational environment by employing an operational simulation.
195-210
Schumann, Benjamin
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Ferraro, Mario
bb685634-3a36-49dd-bd2e-ade3f475796c
Surendra, Amrith
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Scanlan, James P.
7ad738f2-d732-423f-a322-31fa4695529d
Fangohr, Hans
9b7cfab9-d5dc-45dc-947c-2eba5c81a160
April 2014
Schumann, Benjamin
04102357-2f80-4a4f-b2d3-ad34c3b51a05
Ferraro, Mario
bb685634-3a36-49dd-bd2e-ade3f475796c
Surendra, Amrith
a8965a4f-47aa-4817-82d2-ac091cdb7d08
Scanlan, James P.
7ad738f2-d732-423f-a322-31fa4695529d
Fangohr, Hans
9b7cfab9-d5dc-45dc-947c-2eba5c81a160
Schumann, Benjamin, Ferraro, Mario and Surendra, Amrith et al.
(2014)
Better design decisions through operational modeling during the early design phases.
Journal of Aerospace Information Systems, 11 (4), .
(doi:10.2514/1.I010149).
Abstract
This work presents an operational simulation based on a unique mission ontology that enables recreating any aviation scenario using a small set of parameters. The tool is designed to suit the early design phases where time pressures, uncertainties and knowledge gaps peak. It is embedded in a stack of software allowing early design phase optimization based on operational constraints. This stack was used to design and build several Unmanned Aerial Vehicles. Two case studies demonstrate how the tool can act as a decision support or optimization tool, leading to improved designs and better operations. It is found that early design decisions can be based on a more rigorous analysis and that it is possible to optimize both the design and the operational environment by employing an operational simulation.
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Published date: April 2014
Organisations:
Computational Engineering & Design Group
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Local EPrints ID: 357295
URI: http://eprints.soton.ac.uk/id/eprint/357295
PURE UUID: ffce5dd8-b289-4669-9658-b5b1488c8fc3
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Date deposited: 02 Oct 2013 13:33
Last modified: 15 Mar 2024 03:03
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Author:
Benjamin Schumann
Author:
Amrith Surendra
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